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Inductive vs. Deductive Logic

An argument is deductive if its conclusion necessarily follows from its premises—otherwise it is inductive. In an inductive argument, the author presents the premises as evidence or reasons for the conclusion. The validity of the conclusion depends on how compelling the premises are. Unlike deductive arguments, the conclusion of an inductive argument is never certain. The truth of the conclusion can range from highly likely to highly unlikely. In reasonable arguments, the conclusion is likely. In fallacious arguments, it is improbable. We will study both reasonable and fallacious arguments.


We will classify the three major types of inductive reasoning—generalization, analogy, and causal— and their associated fallacies.


Generalization and analogy, which we consider in the next section, are the main tools by which we accumulate knowledge and analyze our world. Many people define generalization as ““inductive reasoning.”” In colloquial speech, the phrase ““to generalize”” carries a negative connotation. To argue by generalization, however, is neither inherently good nor bad. The relative validity of a generalization depends on both the context of the argument and the likelihood that its conclusion is true. Polling organizations make predictions by generalizing information from a small sample of the population, which hopefully represents the general population. The soundness of their predictions (arguments) depends on how representative the sample is and on its size. Clearly, the less comprehensive a conclusion is the more likely it is to be true. For example,


During the late seventies when Japan was rapidly expanding its share of the American auto market, GM surveyed owners of GM cars and asked them whether they would be more willing to buy a large, powerful car or a small, economical car. Seventy percent of those who responded said that they would prefer a large car. On the basis of this survey, GM decided to continue building large cars. Yet during the ‘‘80’’s, GM lost even more of the market to the Japanese.


The argument generalizes from the survey to the general car-buying population, so the reliability of the projection depends on how representative the sample is. Suppose eighty percent of the owners who wanted big cars and only 40 percent of the owners who wanted small cars replied to the survey. Then the survey would not represent the entire public and therefore would not be reliable.


To argue by analogy is to claim that because two things are similar in some respects, they will be similar in others. Medical experimentation on animals is predicated on such reasoning. The argument goes like this: the metabolism of pigs, for example, is similar to that of humans, and high doses of saccharine cause cancer in pigs. Therefore, high doses of saccharine probably cause cancer in humans.


Clearly, the greater the similarity between the two things being compared, the stronger the argument will be. Also, the less ambitious the conclusion, the stronger the argument will be. The argument above would be strengthened by changing probably to may. It can be weakened by pointing out the dissimilarities between pigs and people.


The following words usually indicate that an analogy is being drawn:


Analogy Indicators







compared to

as with

just as . . . so too . . .


Often, however, a writer will use an analogy without flagging it with any of the above words.


Just as the fishing line becomes too taut, so too the trials and tribulations of life in the city can become so stressful that one’’s mind can snap.


The argument compares the tautness in a fishing line to the stress of city life; it then concludes that the mind can snap just as a fishing line can.

Causal Reasoning

Of the three types of inductive reasoning we will discuss, causal reasoning is both the weakest and the most prone to fallacy. Nevertheless, it is a useful and common method of thought.


To argue by causation is to claim that one thing causes another. A causal argument can be either weak or strong depending on the context. For example, to claim that you won the lottery because you saw a shooting star the night before is clearly fallacious. However, most people believe that smoking causes cancer because cancer often strikes those with a history of cigarette use. Although the connection between smoking and cancer is virtually certain, as with all inductive arguments, it can never be 100 percent certain. Cigarette companies have claimed that there may be a genetic predisposition in some people to both develop cancer and crave nicotine. Although this claim is highly improbable, it is conceivable.


There are two common fallacies associated with causal reasoning:


1. Confusing Correlation with Causation.


To claim that A caused B merely because A occurred immediately before B is clearly questionable. It may be only coincidental that they occurred together, or something else may have caused them to occur together. For example, the fact that insomnia and lack of appetite often occur together does not mean that one necessarily causes the other. They may both be symptoms of an underlying condition.


2. Confusing Necessary Conditions with Sufficient Conditions.


A is necessary for B means ““B cannot occur without A.”” A is sufficient for B means ““A causes B to occur, but B can still occur without A.”” For example, a small tax base is sufficient to cause a budget deficit, but excessive spending can cause a deficit even with a large tax base. A common fallacy is to assume that a necessary condition is sufficient to cause a situation. For example, to win a modern war it is necessary to have modern, high-tech equipment, but it is not sufficient, as Iraq discovered in the Persian Gulf War.

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